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    AI Marketing Frameworks

    Structured models for making better decisions about AI in marketing.

    Practical models, decision systems and strategic frameworks for planning, implementing, evaluating and scaling AI in marketing. Each framework shows its model first, explains every part, and then becomes a small tool you can use on the spot.

    What are you trying to solve?

    All frameworks

    Fifteen frameworks in five groups. Search across every step and term, or filter by category and type of tool.

    Strategy and planning

    Decide where AI fits, how far you are and what your stack needs.

    1. Stage guide

      Build an AI strategy

      AI Marketing Adoption Framework

      Seven stages that take a marketing team from first ideas to governed, scaled AI use.

      1. Discover
      2. Assess
      3. Prioritise
      4. Pilot
      5. Measure
    2. Assessment

      Assess AI maturity

      AI Marketing Maturity Framework

      Five levels and eight dimensions to see how far AI is embedded in your marketing.

      1. Exploring
      2. Assisted
      3. Integrated
      4. Automated
      5. AI-native
    3. Assessment

      Design your AI stack

      AI Marketing Stack Framework

      Six layers every AI marketing stack needs, from data to governance.

      1. Governance
      2. Measurement
      3. Workflows
      4. Tools
      5. Models

    Opportunities and value

    Choose the right opportunities and tools, and prove the value.

    1. Decision tool

      Find AI opportunities

      AI Use-Case Prioritisation Framework

      Score impact against effort to decide which AI projects to run first.

      1. Quick wins
      2. Strategic projects
      3. Experiments
      4. Lower priority
    2. Calculator

      Calculate AI ROI

      AI Marketing ROI Framework

      A calculation chain from current process cost to net AI value.

      1. Current process cost
      2. AI implementation cost
      3. Time saved
      4. Additional output
      5. Performance improvement
    3. Decision tool

      Evaluate an AI tool

      AI Tool Evaluation Framework

      Twelve criteria to evaluate any AI product the same way, and compare up to three side by side.

      1. Use-case fit
      2. Output quality
      3. Reliability
      4. Ease of use
      5. Integrations

    Workflows and automation

    Design processes and decide what people and AI each do.

    1. Builder

      Design an AI workflow

      AI Workflow Design Framework

      Eight steps every AI workflow needs before you automate it.

      1. Trigger
      2. Input
      3. AI task
      4. Validation
      5. Human review
    2. Decision tool

      Check automation readiness

      AI Automation Readiness Framework

      Six conditions a process must meet before AI runs it on its own.

      1. Process stability
      2. Volume
      3. Data quality
      4. Error cost
      5. Reversibility
    3. Decision tool

      Decide what to automate

      Human + AI Collaboration Framework

      Decide for each task who leads: a person, the AI, or a system under controls.

      1. Human
      2. AI

    Content and AI search

    Create content, prompts and campaigns that work, also in AI search.

    1. Assessment

      Improve AI content

      AI Content Quality Framework

      Nine quality dimensions to check AI-assisted content before it goes out.

      1. Accuracy
      2. Originality
      3. Relevance
      4. Expertise
      5. Brand alignment
    2. Assessment

      Improve AI search visibility

      AI Visibility Framework (GEO)

      Seven practical checks to help AI search find, understand and cite a page.

      1. Discoverability
      2. Understanding
      3. Retrievability
      4. Trust
      5. Citability
    3. Builder

      Build better prompts

      Prompt Design Framework

      Eight building blocks for prompts that give consistent, usable results.

      1. Role
      2. Objective
      3. Context
      4. Input
      5. Constraints
    4. Builder

      Plan an AI campaign

      AI Campaign Framework

      Ten steps for running a marketing campaign with AI in the right places.

      1. Objective
      2. Audience
      3. Insight
      4. Message
      5. Channel

    Testing and governance

    Test changes properly and keep AI safe, legal and on brand.

    1. Builder

      Run AI experiments

      AI Experimentation Framework

      Eight steps to prove an AI change works, instead of assuming it does.

      1. Problem
      2. Hypothesis
      3. AI intervention
      4. Baseline
      5. Experiment
    2. Assessment

      Set up AI governance

      AI Governance Framework

      Six control areas that keep AI in marketing safe, legal and on brand.

      1. Policy
      2. Roles
      3. Data
      4. Disclosure
      5. Risk tiers

    Download the frameworks

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    Frameworks

    Strategy and planning

    Opportunities and value

    Workflows and automation

    Content and AI search

    Testing and governance

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    How the sections work together

    Guides
    Teach you how.
    Templates
    Give you something to fill in and use.
    Frameworks
    Give you a method for thinking and deciding.
    Comparisons
    Help you choose between tools.
    Workflows
    Show how tasks connect and run.